Study population. National Health and Nutrition Examination Survey (NHANES) is a cross-sectional, nationally representative survey in the United States conducted annually by CDC's National Center for Health Statistics (CDC/NCHS). A detailed description of the study design can be found elsewhere [12]. The survey uses a multistage stratified probability sample based on selected counties, blocks, households, and persons within households. Survey interviews were conducted in participants' homes by well-trained professionals, while extensive physical examinations, including blood and urine collection, were conducted at mobile exam centers.
The present analysis included five waves of the NHANES from 2007 to 2016, which were publicly shared and downloaded from the CDC official website and combined according to the NHANES tutorials. There were 50588 subjects from these years, of which 6598 were aged between 12 and 19 years. First, we excluded subjects who were serologically positive for hepatitis B virus or hepatitis C virus. We then excluded samples from the analysis that did not have complete records including liver function test and phthalate. Further, missing data samples for covariables such as poverty income ratio, body mass index and physical activity were excluded. Finally, 6 samples with total bilirubin (TBIL) test value of 0 were deleted, and a total of 1650 adolescents were selected as final samples. (Supplementary Figure 1).
Liver function measure outcomes. Fasting blood samples were collected in NHANES participants aged 12 years and older at a mobile examination center. The samples were refrigerated and transported to the central laboratory for analysis of serum liver function indicators using the Beckman Coulter DxC800 Synchron clinical system [13].
The liver is rich in alanine aminotransferase (ALT) and aspartate aminotransferase (AST). Serum levels of these two enzymes rise when hepatocytes necrosis or liver cell membrane damage [14]. AST/ALT ratio is used for differential diagnosis of acute and chronic liver diseases. The liver is the only place where albumin (ALB) is synthesized. When liver function is impaired, serum albumin (ALB) and total protein (TP) levels decrease [15]. Alkaline phosphotase (ALP) and Gamma glutamyl transferase (GGT) are markers of cholestasis [16]. The liver has the functions of uptake, combination and excretion of bilirubin metabolism. The disorder of one or more functions can lead to the increase of total bilirubin (TBIL) [17].
Measurement of phthalate. Phthalate metabolites were measured in spot urine samples from a third of study subjects randomly selected from participants six years of age and older. The collected samples were frozen at -20 ℃ and then shipped to the CDC's National Center for Environmental Health for analysis. Urine specimens were processed using high performance liquid chromatography-electrospray ionization-tandem mass spectrometry (HPLC-ESI-MS/MS) for the quantitative detection of phthalate metabolites [13].
We selected 12 metabolites tested in all 5 rounds and excluded phthalate metabolites whose measured values were more than 40% below the detection limit (LOD). The remaining 11 urinary phthalate metabolites used in our study were mono-(carboxyisononyl) phthalate (MCNP), mono-(carboxyisoctyl) phthalate (MCOP), mono-2-ethyl-5-carboxypentyl phthalate (MECPP), mono-n-butyl phthalate (MnBP), mono-(3-carboxypropyl) phthalate (MCPP), mono-ethyl phthalate (MEP), mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono-(2-ethylhexyl phthalate (MEHP), mono-isobutyl phthalate (MiBP), mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP), and mono-benzyl phthalate (MBzP). Phthalate metabolites concentrations below LODs were replaced with LOD divided by the square root of two.
Concentrations of MECPP, MEHHP, MEHP and MEOHP were divided by their respective molar weight (MW) to obtain the molar equivalent. We summed the molar equivalents of these metabolites and multiplied by the molar weight of MEHP (MW= 278) to obtain ΣDEHP metabolites [18].
Measurements of Covariates. Covariates were selected as potential confounders by referencing to previous publications [19, 20]. Sociodemographic covariates included gender (Male, Female), race (Non-Hispanic White, Non-Hispanic Black, Mexican American, Other Hispanic, Other/Mixed), education (Less than high school, High School graduate or GED, More than High), and poverty income ratio (PIR≤1, PIR>1). Lifestyle covariate included physical activity. It was measured by respondents' self-reported time spent in vigorous or moderate recreational physical activity. The dichotomous variables for physical activity were classified as “inactive” (<10 min per week) and “activity” (≥10 min per week). Examination results covariate included body mass index (BMI). BMI was calculated as weight (kg) /height2 (m2) measured in the physical examination and categorized into three levels: < 25 kg/m2 (Normal/Underweight), 25-<30 kg/m2 (overweight) and ≥30 kg/m2 (obese) [21].
Statistical analysis. Demographic characteristics were reported as percentages. Phthalate metabolite concentrations and liver function levels were described in the quartile range. We used urine creatinine to adjust the concentrations of phthalate metabolites in all statistical analyses. Creatinine-adjusted phthalate metabolites concentrations and indicators of liver function were natural log-transformed to make them normally distributed. Spearman’s coefficients were used to test the pairwise correlations of phthalate metabolite concentrations (Supplementary Table 2). We performed survey-weighted linear regression to assess the associations of the urinary phthalate metabolites with indicators of liver function. We additionally performed stratification analyses by gender group. Benjamini-Hochberg false discovery rate (FDR) correction was used to adjust P values to adjust for multiple testing.
We further performed a BKMR analysis to evaluate the joint effects of exposure to phthalate metabolite mixtures on indicators of liver function [22]. We fitted separate BKMR models for each index of liver function according to the following models:
Yi = h(ΣDEHPi, MCNPi, MCOPi, MnBPi, MCPPi, MEPi, MiBPi, MBzPi)+βzi +ei. The h() is an exposure–response function, which can incorporate non-linear relationships and interactions among the mixture components; β is coefficient; zi is covariates. BKMR identifies the relative importance of individual exposure variables to the joint effects by providing an estimate of posterior inclusion probabilities (PIPs). The PIP threshold was 0.5 in this study [23]. BKMR facilitates visualization of results for the effect of single exposure and interactions between exposure and outcome. First, the cumulative effect of exposure to the combination of eight phthalate metabolites on indicators of live function in adolescents was evaluated. Then, the effects of a single exposure to a single phthalate metabolite were calculated when other phthalate metabolites were fixed to their median level. Lastly, the joint effect of two phthalate metabolites were studied by plotting a dose-response relationship of one phthalate metabolite at different quantiles of another phthalate metabolite, based on the median level of the other phthalate metabolites.
All models were adjusted for poverty income ratio, BMI, age, gender, race, education, and physical activity. All analyses were performed using phthalate-specific subsample weight as recommended by NCHS, to account for the complex sampling design and non-response of NHANES. Weights for combined NHANES survey cycles were calculated according to NHANES guidelines. All statistical analyses were performed using R 3.5.3. All test values were 2-sided and P <0.05 was considered significant.